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Author:

Ningning, Li (Ningning, Li.) | Su, Song (Su, Song.)

Indexed by:

EI Scopus

Abstract:

It is a critical problem in the neural network adaptive control system to attenuate the influence of external disturbance or unmodeled dynamics and improve the robustness. In this paper, a novel robust adaptive control based on neural network for unknown nonlinear dynamical systems with bounded disturbances or unmodeled dynamics was proposed. It was realized by using adaptive forecasting and the recursive forgetting factor least square method, also the stability of system was guaranteed by a robust controller. The validity of this control strategy was demonstrated via simulation results. © 2006 IEEE.

Keyword:

Robustness (control systems) Robust control Least squares approximations Neural networks Adaptive control systems Nonlinear systems Uncertain systems Dynamical systems

Author Community:

  • [ 1 ] [Ningning, Li]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100022
  • [ 2 ] [Su, Song]Department of Information Sciences, National Natural Science Foundation of China, Beijing 100085

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Source :

Year: 2006

Volume: 1

Page: 2388-2392

Language: Chinese

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 7

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